How to calculate the output of this neural network?
The neural Network in the image is a &quot;Recurrent Neural Network&quot;(RNN). Because of the connection leading backward from h10 to h01, h10 has to be a &quot;memory node&quot; (mn), meaning it can store its value from the previous input. The basic functionality of an RNN can be seen in this animation:



Your example:
In the beginning, the storage of the mn is initialized with a value, probably 0.
Now the first input is fed into network:

i0 = 2
i1 = 3
h00 = (i0 * 0.4) = 0.8
h01 = (i1 * -0.9) + (&quot;the stored value of h10&quot; * 1.2) = -2.7
(&quot;the stored value of h10&quot; in the first run is 0.)
h10 = (h00 * 0.85) + (h01 * -0.2) = 1.22
out = (h10 * 0.3) + (h01 * 0.1) =  0.096

Now you can feed the next input through the network and use -2.7 as &quot;the stored value of h10&quot; and so on. You can also add an activation function as you would for any other NN.